Liese Juliane, Peveling-Oberhag Jan, Doering Claudia, Schnitzbauer Andreas A, Herrmann Eva, Zangos Stephan, Hansmann Martin L, Moench Christian, Welker Martin W, Zeuzem Stefan, Bechstein Wolf O, Ulrich Frank
Department of General and Visceral Surgery, University Hospital Frankfurt, Goethe University, Frankfurt, Germany.
Department of Internal Medicine 1, University Hospital Frankfurt, Goethe University, Frankfurt, Germany.
Transpl Int. 2016 Mar;29(3):369-80. doi: 10.1111/tri.12733. Epub 2016 Jan 28.
With favourable 5-year survival rates up to 75%, liver transplantation (LT) is the treatment of choice for hepatocellular carcinoma (HCC). Nonetheless, tumour recurrence after LT remains a challenge. The aim of this retrospective study was to develop a predictive score for tumour recurrence after LT by combining clinical parameters with HCC biomarkers (microRNA). A microRNA (miRNA) microarray analysis was used to compare miRNA expression patterns in tissue samples of 40 patients with and without HCC recurrence after LT. In a screening cohort (n = 18), the miRNA analysis identified significant differences in the expression of 13 miRNAs in patients with tumour recurrence. Using the most significant miRNAs in this screening cohort, we could develop a predictive score, which combined the expression levels of miR-214, miR-3187 and the Milan criteria, and we could define low- and high-risk groups for tumour recurrence and death. The above score was evaluated in a second and independent cohort (n = 22). In contrast to the Milan criteria alone, this score was significantly associated with tumour recurrence. Our analysis indicated that the use of a specific miRNA expression pattern in combination with a limited tumour burden as defined by the Milan criteria may lead to a more accurate prediction of tumour recurrence.
肝移植(LT)是肝细胞癌(HCC)的首选治疗方法,其5年生存率高达75%。尽管如此,肝移植后的肿瘤复发仍然是一个挑战。这项回顾性研究的目的是通过将临床参数与HCC生物标志物(微小RNA)相结合,开发一种预测肝移植后肿瘤复发的评分系统。使用微小RNA(miRNA)微阵列分析来比较40例肝移植后有或无HCC复发患者的组织样本中的miRNA表达模式。在一个筛查队列(n = 18)中,miRNA分析确定了肿瘤复发患者中13种miRNA表达的显著差异。利用该筛查队列中最显著的miRNA,我们开发了一种预测评分系统,该系统结合了miR-214、miR-3187的表达水平和米兰标准,并且我们可以定义肿瘤复发和死亡的低风险和高风险组。上述评分系统在第二个独立队列(n = 22)中进行了评估。与单独的米兰标准相比,该评分系统与肿瘤复发显著相关。我们的分析表明,结合特定的miRNA表达模式和米兰标准定义的有限肿瘤负荷,可能会更准确地预测肿瘤复发。